A nonmonotone adaptive projected gradient method for primal-dual total variation image restoration

2014 ◽  
Vol 103 ◽  
pp. 242-249 ◽  
Author(s):  
Gaohang Yu ◽  
Wei Xue ◽  
Yi Zhou
Keyword(s):  
Image Restoration ◽  
Total Variation ◽  
Gradient Method ◽  
Projected Gradient Method ◽  
Projected Gradient ◽  
Primal Dual

An Inexact Projected Gradient Method for Sparsity-Constrained Quadratic Measurements Regression

2019 ◽  
Vol 36 (02) ◽  
pp. 1940008
Author(s):  
Jun Fan ◽  
Liqun Wang ◽  
Ailing Yan
Keyword(s):  
Gradient Method ◽  
Least Squares Method ◽  
Optimal Solution ◽  
High Dimensional ◽  
Sparse Signals ◽  
Projected Gradient Method ◽  
Constrained Least Squares ◽  
Projected Gradient ◽  
High Dimensional Case ◽  
Noisy Measurements

In this paper, we employ the sparsity-constrained least squares method to reconstruct sparse signals from the noisy measurements in high-dimensional case, and derive the existence of the optimal solution under certain conditions. We propose an inexact sparse-projected gradient method for numerical computation and discuss its convergence. Moreover, we present numerical results to demonstrate the efficiency of the proposed method.

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